1. data-debt-ai-telecom-exchange-hall.jpg | Telecom data executive walks through a historic telephone exchange where legacy switching frames meet modern equipment
心を動かす会話

Powering Telecom Data for Tomorrow’s AI Operations

Turn fragmented network, customer and operations data into a governed foundation, so your AI moves from pilots into the P&L.
会議のスケジューリング
AI ambition is running ahead of the data underneath it.
WHY THIS DATA DEBT CHALLENGE?
Six in ten expect AI revenue, only one in four sees a path to scale Mergers, vendor-specific network domains and separate OSS/BSS stacks left your data hard for AI to use.

Only a third of operators say their data is fully governed. Every new pilot builds its own pipeline, and costs keep rising.

主なメリット
Clean, governed data behind every use Case

A shared foundation, organized as data products with named owners, cuts the time and cost of each new AI use case and keeps results traceable for your board and regulators.

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Faster path to production

Your teams reuse certified data instead of building a new pipeline for each project, so use cases go live sooner.

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Lower cost after the first use case

The data platform, quality rules and access controls are shared, so every new use case costs less to build and run.

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One version of the facts

Network, IT and customer data sit in one common telecom data model, so care, assurance and network planning work from the same numbers.

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Compliance built into the platform

Lineage, privacy and data residency controls keep sensitive data in the jurisdictions where regulation requires it, under your control.

NTTデータのサポート体制は?

01
Size the data debt

We assess network, OSS/BSS and customer data sources against your priority AI use cases and put a figure on what poor data costs you today.

3. data-debt-ai-legacy-equipment-inventory.jpg | Data consultant and network engineer take inventory of legacy telecom equipment in a basement storage room
02
Design the target architecture

A data fabric connects your platforms where they already run, on a common telecom data model, so you migrate step by step with no lock-in to one vendor.

4. data-debt-ai-architecture-sketch.jpg | Data architect sketches a layered data architecture on paper while a colleague points at one layer
03
Build data products with owners

We start with network inventory, service assurance and billing, each with quality rules, service levels and an accountable owner on your side.

5. data-debt-ai-data-owners-standup.jpg | Three telecom data product owners hold a quick stand-up meeting on a glass stairwell landing
04
Automate governance and sovereignty

The platform enforces lineage, access policies, privacy and residency rules, so compliance stops depending on manual checks.

6. data-debt-ai-sovereign-data-center.jpg | Compliance officer walks toward a data center in a green landscape with wind turbines on the hills
05
Industrialize AI on top

MLOps and LLMOps move priority use cases from pilot to production, and we track each one against a business outcome agreed before launch.

実証済みの効果
One governed data foundation, many AI use cases

Consolidate network and customer data into governed data products once, then build every new AI use case on top of them.

重要な結果
Measures Agreed Before the First Launch

Your business signs off on every measure before the first use case goes live, and we report results use case by use case.

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Time to production

Track how long a new AI use case takes to go from approved idea to live operation.

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Governed data coverage

Measure the share of your priority data domains under full governance, with owners, quality rules and lineage.

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Cost per use case

Follow the full cost of each AI use case, including the run cost of the data platform underneath.

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Operational outcomes

Watch service activation lead time, order fallout, cost to serve, mean time to repair and churn where the data is in use.

How much of your AI roadmap is waiting on data you don’t yet trust?

Clearing data debt turns AI from a series of isolated pilots into a lasting operating advantage.

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